The declining water level in Lake Urmia has become a significant issue for Iranian policy and decision makers. This lake has been experiencing an abrupt decrease in water level and is at real risk of becoming a complete saline land. Because of its position, assessment of changes in the Lake Urmia is essential. This study aims to evaluate changes in the water level of Lake Urmia using the space-borne remote sensing and GIS techniques. Therefore, multispectral Landsat 7 ETM+ images for the years 2000, 2010, and 2017 were acquired. In addition, precipitation and temperature data for 31 years between 1986 and 2017 were collected for further analysis. Results indicate that the increased temperature (by 19%), decreased rainfall of about 62%, and excessive damming in the Urmia Basin along with mismanagement of water resources are the key factors in the declining water level of Lake Urmia. Furthermore, the current research predicts the potential environmental crisis as the result of the lake shrinking and suggests a few possible alternatives. The insights provided by this study can be beneficial for environmentalists and related organizations working on this and similar topics.
China prioritizes ecological civilization construction and embraces the concept of "lucid waters and lush mountains are invaluable assets." Great achievements have been made in ecological protection and restoration through implementing a series of policies and projects. This paper reviews the history of ecological restoration in China and the current development of the "integrated protection and restoration project of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts (IPRP)." Furthermore, the characteristics of IPRP were systematically elaborated from the perspectives of the ecological civilization thought, the policy management, and the key scientific issues. Also, the current achievements were summarized in the fields of national ecological space management, biodiversity conservation, and ecological protection and restoration. Existing challenges in management policy, scientific issues, and engineering practices were highlighted. Future perspectives include ecological space control, nature-based Solutions, biodiversity big data platform, modern techniques, and value realization mechanisms of ecological products.
The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.
This report describes the whole-genome sequence of an alkalitolerant microcystin-degrading bacterium, Sphingopyxis sp. strain C-1, isolated from a lake in China.
Very little work has determined the relative importance of uncontrolled environmental factors for affecting fish biology, and how these might influence gillnet catches. This study addresses this deficit for an important Southeast Asian cyprinid (Barbonymus schwanenfeldii). Fish were caught monthly for 12 months using gillnets of three different mesh sizes, each of which was deployed in duplicate at the surface of one of three randomly selected sites in Lake Kenyir, Malaysia, concurrent with determining various environmental parameters and the abundance of phytoplankton (chlorophyll-a). Results indicated that growth co-efficient of B. schwanenfeldii was positively influenced by dissolved oxygen and negatively influenced by total inorganic nitrogen, whereas an opposite result was observed in case of the hepatosomatic index of fish. Water turbidity was a limiting factor only for small fish (mean total length: 15.74±1.10 cm). B. schwanenfeldii could best be caught during the period of high phytoplankton abundance or at the location of high phytoplankton density in the water. Water temperature negatively influenced the gillnet catches of the fish. The remaining environmental factors such as water depth, pH, and phosphate had a weak and insignificant influence (P >0.05) on the biology and gillnet catches of fish. The observed results can be very useful for the ecological monitoring and conservation plans for this species in relation to climate change. Furthermore, the utility of the similar data for other species would be useful not only for regional but also for international fishery by optimizing catches considering environmental conditions.
Several research efforts have been conducted to monitor and analyze the impact of environmental factors on the heavy metal concentrations and physicochemical properties of water bodies (lakes and rivers) in different countries worldwide. This article provides a general overview of the previous works that have been completed in monitoring and analyzing heavy metals. The intention of this review is to introduce the historical studies to distinguish and understand the previous challenges faced by researchers in analyzing heavy metal accumulation. In addition, this review introduces a survey on the importance of time increment sampling (monthly and/or seasonally) to comprehend and determine the rate of change of different parameters on a monthly and seasonal basis. Furthermore, suggestions are made for future research to achieve more understandable figures on heavy metal accumulation by considering climate conditions. Thus, the intent of the current study is the provision of reliable models for predicting future heavy metal accumulation in water bodies in different climates and pollution conditions so that water management can be achieved using intelligent proactive strategies and artificial neural network (ANN) techniques.
Studies that associate environmental parameters with aquatic organisms in man-made lakes remain limited by accessibility and interest particularly in many Asian countries. With missed opportunities to monitor environmental transitions at Lake Kenyir, our knowledge of lake transition is restricted to the non-mixing shallow waters only. Triplicate monthly benthic invertebrate samples were collected concurrently with various environmental parameters at three locations (zones A-C) of Kenyir Lake, Malaysia. Our results affirmed that the northeast part of Lake Kenyir is oligotrophic. Abundance of phytoplankton, total suspended solids, phosphate, nitrite and nitrate drive the abundance of various groups of benthic invertebrates. All of these extrinsic variables (except phosphate) negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Polychaeta, Oligochaeta, Bivalvia, Gastropod, Isopoda and Copepod in all zones. Phosphate negatively influenced the density of Trichoptera and positively influenced (P<0.05) the densities of Oligochaeta, Bivalvia and Copepod. Its influences on the Polychaeta, Gastropod and Isopoda densities were zone-specific. Overall, seasons equally influenced the relationships between extrinsic and response variables in all zones. The results of this study are useful to evaluate the lake's environmental quality, in conservation and in similar projects involving environmental handling, monitoring and recovery.
The Great Lakes are critical freshwater sources, supporting millions of people, agriculture, and ecosystems. However, climate change has worsened droughts, leading to significant economic and social consequences. Accurate multi-month drought forecasting is, therefore, essential for effective water management and mitigating these impacts. This study introduces the Multivariate Standardized Lake Water Level Index (MSWI), a modified drought index that utilizes water level data collected from 1920 to 2020. Four hybrid models are developed: Support Vector Regression with Beluga whale optimization (SVR-BWO), Random Forest with Beluga whale optimization (RF-BWO), Extreme Learning Machine with Beluga whale optimization (ELM-BWO), and Regularized ELM with Beluga whale optimization (RELM-BWO). The models forecast droughts up to six months ahead for Lake Superior and Lake Michigan-Huron. The best-performing model is then selected to forecast droughts for the remaining three lakes, which have not experienced severe droughts in the past 50 years. The results show that incorporating the BWO improves the accuracy of all classical models, particularly in forecasting drought turning and critical points. Among the hybrid models, the RELM-BWO model achieves the highest level of accuracy, surpassing both classical and hybrid models by a significant margin (7.21 to 76.74%). Furthermore, Monte-Carlo simulation is employed to analyze uncertainties and ensure the reliability of the forecasts. Accordingly, the RELM-BWO model reliably forecasts droughts for all lakes, with a lead time ranging from 2 to 6 months. The study's findings offer valuable insights for policymakers, water managers, and other stakeholders to better prepare drought mitigation strategies.
Fauna of Cladocera (Crustacea: Branchiopoda) of Sabah state of Malaysia, Borneo Island, was evaluated for the first time. Samples from 40 locations were studied, and 31 species of Cladocera were revealed, including three species of Sididae, one species of Daphnidae, one species of Moinidae, four species of Macrothricidae, two species of Ilyocryptidae, and 20 species of Chydoridae. One species of Ilyocryptidae, Ilyocryptus yooni Jeong, Kotov and Lee, 2012, is recorded for Malaysia for the first time, and one more, Anthalona sp., is probably new for science. Of 31 species recorded for Sabah, only three are true planktonic species and 28 are substrate-associated species. Absence of large natural lakes, habitats with most rich cladoceran fauna, can be an important factor limiting diversity of Cladocera in Sabah.
Dickeya sp. strain 2B12 was isolated from a freshwater lake in Malaysia. Here, we report the draft genome sequence of Dickeya sp. 2B12 sequenced by the Illumina MiSeq platform. With the genome sequence available, this genome sequence will be useful for the study of quorum-sensing activity in this isolate.
Dickeya chrysanthemi is well known as a plant pathogen that caused major blackleg in the European potato industry in the 1990s. D. chrysanthemi strain L11 was discovered in a recreational lake in Malaysia. Here, we present its draft genome sequence.
This report describes the whole-genome sequence of a microcystin-degrading bacterium, Novosphingobium sp. strain MD-1, isolated from a lake in Japan. The Novosphingobium sp. strain MD-1 genome had a total length of 4,617,766 bp. Moreover, strain MD-1 showed a conserved microcystin-degrading gene cluster (mlrA to mlrF), similar to Sphingopyxis sp. strain C-1.
Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes.
The COVID-19 pandemic has further intensified plastic pollution due to the escalated use of single-use gloves and masks, consequently leading to the widespread presence of microplastics (MPs) and nanoplastics (NPs) in major rivers and lakes worldwide. Macrobrachium rosenbergii has become an important experimental subject due to its ecological role and environmental sensitivity. In this study, we sought to comprehend the ramifications of NPs on the widely-distributed freshwater prawn, M rosenbergii, by conducting a detailed analysis of its responses to NPs after both 96 h and 30 days of exposure. The transcriptome analysis revealed 918 differentially expressed unigenes (DEGs) after 30 days of NPs exposure (356 upregulated, 562 downregulated) and 2376 DEGs after 96 h of NPs exposure (1541 upregulated, 835 downregulated). The results of DEGs expression indicated that acute NPs exposure enhanced carbohydrate transport and metabolism, fostering chitin and extracellular matrix processes. In contrast, chronic NPs exposure induced nucleolar stress in M. rosenbergii, impeding ribosome development and mRNA maturation while showing no significant changes in glucose metabolism. Our findings underscore the M. rosenbergii distinct coping mechanisms during acute and chronic NPs exposure, elucidating its vital adaptive strategies. These results contribute to our understanding of the ecological implications of NPs pollution and its impact on aquatic animals.
The present study aims to identify the Acanthamoeba genotypes and their pathogenic potential in three recreational lakes in Malaysia. Thirty water samples were collected by purposive sampling between June and July 2022. Physical parameters of water quality were measured in situ while chemical and microbiological analyses were performed in the laboratory. The samples were vacuum filtered through nitrate filter, cultured onto non-nutrient agar and observed microscopically for amoebic growth. DNAs from positive samples were extracted and made to react with polymerase chain reaction using specific primers. Physiological tolerance tests were performed for all Acanthamoeba-positive samples. The presence of Acanthamoeba was found in 26 of 30 water samples by PCR. The highest rate in lake waters contaminated with amoeba was in Biru Lake (100%), followed by Titiwangsa Lake (80%) and Shah Alam Lake (80%). ORP, water temperature, pH and DO were found to be significantly correlated with the presence of Acanthamoeba. The most common genotype was T4. Temperature- and osmo-tolerance tests showed that 8 (30.8%) of the genotypes T4, T9 and T11 were highly pathogenic. The presence of genotype T4 in habitats related to human activities supports the relevance of this amoeba as a potential public health concern.
Thermal structure and water quality in a large and shallow lake in Malaysia were studied between January 2012 and June 2013 in order to understand variations in relation to water level fluctuations and in-stream mining activities. Environmental variables, namely temperature, turbidity, dissolved oxygen, pH, electrical conductivity, chlorophyll-A and transparency, were measured using a multi-parameter probe and a Secchi disk. Measurements of environmental variables were performed at 0.1 m intervals from the surface to the bottom of the lake during the dry and wet seasons. High water level and strong solar radiation increased temperature stratification. River discharges during the wet season, and unsustainable sand mining activities led to an increased turbidity exceeding 100 NTU, and reduced transparency, which changed the temperature variation and subsequently altered the water quality pattern.
This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.
We report the detection of genomic signatures of giant viruses (GVs) in the metagenomes of three environment samples from Mumbai, India, namely, a pre-filter of a household water purifier, a sludge sample from wastewater treatment plant (WWTP), and a drying bed sample of the same WWTP. The de novo assembled contigs of each sample yielded 700 to 2000 maximum unique matches with the GV genomic database. In all three samples, the maximum number of reads aligned to Pandoraviridae, followed by Phycodnaviridae, Mimiviridae, Iridoviridae, and other Megaviruses. We also isolated GVs from every environmental sample (n = 20) we tested using co-culture of the sample with Acanthomoeba castellanii. From this, four randomly selected GVs were subjected to the genomic characterization that showed remarkable cladistic homology with the three GV families viz., Mimivirirdae (Mimivirus Bombay [MVB]), Megaviruses (Powai lake megavirus [PLMV] and Bandra megavius [BAV]), and Marseilleviridae (Kurlavirus [KV]). All 4 isolates exhibited remarkable genomic identity with respective GV families. Functionally, the genomes were indistinguishable from other previously reported GVs, encoding nearly all COGs across extant family members. Further, the uncanny genomic homogeneity exhibited by individual GV families across distant geographies indicate their yet to be ascertained ecological significance.
The distribution and abundance of zooplankton species of Harapan and Aman
Lakes were investigated in relation to physical parameters and chlorophyll-a content. Both
lakes were characterised by the occurrence of algal bloom problem. The composition of
zooplankton was collected at monthly intervals from November 2013 to February 2014.
The total number of taxa in Harapan and Aman Lakes were 23 and 27, respectively.
Rotifera was the highest abundance group represent 64% of the total species recorded
followed by Copepoda (29%) and Cladocera (7%). Three dominant zooplankton that been
recorded in both the lakes are Brachionus forficula, Brachionus nilsoni, and Trichocerca
sp. High abundance of these species indicates that the lakes are eutrophic water bodies.
Overall, zooplankton species distribution and abundance in the study sites are influenced
by various environmental factors such as water transparency and chlorophyll-a content.
Unlike those in the mainland of Southeast Asia, the Cladocera of the Malay Archipelago has not been intensively studied, except for the state of Sabah in the north-eastern part of the Borneo island. This study aimed to complete the inventory of the Cladocera in Sabah by looking at different types of water bodies including oxbow lakes, small lakes, reservoirs, ponds, ditches and paddy fields. From 32 sites examined, 35 species of cladocerans, nine of which were new records to Sabah, were found from 25 localities. With this new finding, the total number of cladoceran species in Sabah increased to 39 species, including five species of Sididae, four species of Daphniidae, one species of Moinidae, five species of Macrothricidae, two species of Ilyocryptidae, and 22 species of Chydoridae. Only 8 % ( three species) of Sabah cladocerans are true planktonic. This study illustrated that most cladocerans were associated with substrates in the littoral zone and thus appropriate sampling methods should be employed in different microhabitats for comprehensive biodiversity assessment.